AI RESEARCH
A High-Resolution Landscape Dataset for Concept-Based XAI With Application to Species Distribution Models
arXiv CS.LG
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ArXi:2604.13240v1 Announce Type: cross Mapping the spatial distribution of species is essential for conservation policy and invasive species management. Species distribution models (SDMs) are the primary tools for this task, serving two purposes: achieving robust predictive performance while providing ecological insights into the driving factors of distribution. However, the increasing complexity of deep learning SDMs has made extracting these insights challenging. To reconcile these objectives, we propose the first implementation of concept-based Explainable AI (XAI) for SDMs.